Josip Juraj Strossmayer University of OsijekFACULTY OF FOOD TECHNOLOGY

Lower level organizational units

Department of Process EngineeringSub-department of Modelling, Optimisation and Automatisation

Place

Osijek

State

Croatia

Scientific field, discipline, subdiscipline

BIOTECHNICAL SCIENCESFood TechnologyEngineering

Study programme type

university

Study level

graduate

Study programme

Process Engineering

Academic title abbreviation

mag. ing. proc.

Genre

master's thesis

Language

Croatian

Defense date

2016-10-10

Parallel abstract (English)

Chemometric methods were used to determine connection among properties of wheat grain and flour produced from 24 cultivars. Cultivars were breed on Agricultural institute Osijek in period of ten years (2005-2014). Following properties were analysed: yield (Y), hectolitre mass (HL), thousand kernel weight (TKW), protein content (P), wet gluten content (WG), gluten index value (GI), sedimentation value (SED), falling number (FN) and flour yield (FY). Following descriptive statistical analysis was applied on experimental set of data: mean value, median, minimum and maximum, standard deviation, coefficient of variability and coefficient of correlation. Following chemometric analysis were applied: principal component analysis (PCA), cluster analysis (CA) and partial least square method (PLSR). Principal component analysis was used for reduction of number of variables, cluster analysis was used for enlightening connections among properties while partial least square regression analysis was used for designing predictive mathematical models. Results show that strong correlations can be used for decreasing number of variables and describing variability of data set with less than nine properties. Using proposed predictive mathematical models based on experimental data makes possible calculating values of rest of properties with precision bigger than 90%.